shiftlayer for discrete count based summaries, descriptive statistics summaries, or shift count summaries
This family of functions specifies the type of summary that is
to be performed within a layer.
count layers are used to create
summary counts of some discrete variable.
desc layers create summary
shift layers summaries the counts of different
changes in states. See the "details" section below for more information.
group_count(parent, target_var, by = vars(), where = TRUE, ...) group_desc(parent, target_var, by = vars(), where = TRUE, ...) group_shift(parent, target_var, by = vars(), where = TRUE, ...)
Required. The parent environment of the layer. This must be the
Symbol. Required, The variable name(s) on which the summary
is to be performed. Must be a variable within the target dataset. Enter
unquoted - i.e. target_var = AEBODSYS. You may also provide multiple
A string, a variable name, or a list of variable names supplied
Call. Filter logic used to subset the target data when performing a summary.
Additional arguments to pass forward
tplyr_layer environment that is a child of the specified
parent. The environment contains the object as listed below.
Count layers allow you to create
summaries based on counting values with a variable. Additionally, this
layer allows you to create n (%) summaries where you're also summarizing
the proportion of instances a value occurs compared to some denominator.
Count layers are also capable of producing counts of nested relationships.
For example, if you want to produce counts of an overall outside group, and
then the subgroup counts within that group, you can specify the target
variable as vars(OutsideVariable, InsideVariable). This allows you to do
tables like Adverse Events where you want to see the Preferred Terms within
Body Systems, all in one layer. Further control over denominators is
available using the function
set_denoms_by and distinct
counts can be set using
Descriptive statistics layers perform summaries on
continuous variables. There are a number of summaries built into Tplyr
already that you can perform, including n, mean, median, standard
deviation, variance, min, max, inter-quartile range, Q1, Q3, and missing
value counts. From these available summaries, the default presentation of a
descriptive statistic layer will output 'n', 'Mean (SD)', 'Median', 'Q1, Q3',
'Min, Max', and 'Missing'. You can change these summaries using
set_format_strings, and you can also add your own summaries
set_custom_summaries. This allows you to implement any
additional summary statistics you want presented.
shift layer displays an endpoint's 'shift' throughout the duration of the
study. It is an abstraction over the count layer, however we have provided
an interface that is more efficient and intuitive. Targets are passed as
named symbols using
dplyr::vars. Generally the baseline is passed
with the name 'row' and the shift is passed with the name 'column'. Both
counts (n) and percentages (pct) are supported and can be specified with
set_format_strings function. To allow for flexibility
when defining percentages, you can define the denominator using the
set_denoms_by function. This function takes variable names and
uses those to determine the denominator for the counts.